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Forecasting Disease Risk for Increased Epidemic Preparedness in Public Health

机译:预测增加公共卫生中流行病防范能力的疾病风险

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摘要

Emerging infectious diseases pose a growing threat to human populations. Many of the world’s epidemic diseases (particularly those transmitted by intermediate hosts) are known to be highly sensitive to long-term changes in climate and short-term fluctuations in the weather. The application of environmental data to the study of disease offers the capability to demonstrate vector–environment relationships and potentially forecast the risk of disease outbreaks or epidemics. Accurate disease forecasting models would markedly improve epidemic prevention and control capabilities. This chapter examines the potential for epidemic forecasting and discusses the issues associated with the development of global networks for surveillance and prediction. Existing global systems for epidemic preparedness focus on disease surveillance using either expert knowledge or statistical modelling of disease activity and thresholds to identify times and areas of risk. Predictive health information systems would use monitored environmental variables, linked to a disease system, to be observed and provide prior information of outbreaks. The components and varieties of forecasting systems are discussed with selected examples, along with issues relating to further development.
机译:新兴的传染病对人类的威胁越来越大。众所周知,世界上许多流行病(尤其是中间宿主传播的流行病)对气候的长期变化和天气的短期波动高度敏感。将环境数据应用于疾病研究,可以证明病媒与环境之间的关系,并有可能预测疾病暴发或流行的风险。准确的疾病预测模型将显着提高流行病的预防和控制能力。本章探讨了流行病预测的潜力,并讨论了与全球监测和预测网络发展有关的问题。现有的全球流行病防范系统侧重于疾病监测,即使用专家知识或疾病活动的统计模型和阈值来确定风险的时间和领域。预测性健康信息系统将使用与疾病系统相关的受监控环境变量进行观察,并提供疫情的先发信息。通过选定的示例讨论了预测系统的组成和种类,以及与进一步开发有关的问题。

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